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| import streamlit as st | |
| import time | |
| from langchain_core.messages import HumanMessage, SystemMessage | |
| from langchain_core.output_parsers import StrOutputParser | |
| parser = StrOutputParser() | |
| from langchain_groq import ChatGroq | |
| import os | |
| st.title('ReciteAI') | |
| st.header('Enter text to complete:') | |
| api_key = st.text_input('Type your Groq API Key') | |
| model = ChatGroq(model="llama3-8b-8192", api_key=api_key) | |
| user_input = st.text_area('Write the description of story', height=200) | |
| max_length = st.slider("Select max story length:", min_value=50, max_value=200, value=100, step=10) | |
| num_sequences = st.selectbox("Select number of stories to generate:", options=[1, 2, 3], index=0) | |
| if st.button('Generate Story'): | |
| with st.spinner('Generating Story...'): | |
| messages = [ | |
| SystemMessage(content="You're an author"), | |
| HumanMessage(content=f"Write {num_sequences} number of stories of {max_length} sentences for {user_input}"), | |
| ] | |
| response = parser.invoke(model.invoke(messages)) | |
| st.write(response) | |
| st.markdown("---") | |
| st.sidebar.markdown("## Guide") | |
| st.sidebar.info("This tool uses GroQ inferencing to generate a story of your provided text. Adjust the sliders to change the story length and number of stories generated. The model is optimized for short to medium length paragraphs.") | |
| st.sidebar.info("By Soham Mhatre") | |
| st.sidebar.markdown("### Examples") | |
| st.sidebar.write("1. Paste a beginning to see how the AI completes it.") | |
| st.sidebar.write("2. Try different settings to see how the story changes.") |